More than 90% of health systems have deployed third-party AI solutions, but only 44% have a dedicated platform for testing those tools before rollout, according to a new report from the Center for Connected Medicine at UPMC and KLAS Research.
The report, “Validation and Trust: How Health Systems Are Testing and Governing AI Solutions,” draws on responses from more than two dozen health system leaders. It examines how organizations are adopting and governing AI amid rapid deployment across administrative and clinical workflows.
Here are four key findings from the report:
- Clinical documentation is the most common AI use case, cited by 52% of respondents, followed by revenue cycle, coding and billing applications at 36%.
- Testing is nearly universal, with 92% of health systems evaluating third-party AI tools before deployment, though validation methods range from formal vendor protocols to informal pilot programs.
- Nearly two-thirds of organizations, 63%, describe their AI strategy as developing or ad hoc rather than fully established. Limited resources, insufficient time and shortages of specialized talent rank as the leading barriers to adoption, and respondents report no consensus on the metrics used to measure AI success.
- Rob Bart, MD, chief medical information officer at UPMC, said in the report that implementation is “only the first step,” with health systems now focused on building the governance structures and testing capabilities needed to ensure AI delivers measurable value.
The Pittsburgh-based Center for Connected Medicine at UPMC and KLAS Research released the report Aug. 6. It can be found here.
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